FPGA architecture comparison for non-conventional signal processing
暂无分享,去创建一个
In the design of a specific application requiring scalar processing and a neural network, it was noticed that the same underlying hardware used to process analog signals could be used as another way to implement neural networks. This paper presents the main ideas behind this design approach, and a comparison in terms of area and processing speeds of both solutions, when using an FPGA as a substrate.
[1] David J. Burr,et al. Experiments on neural net recognition of spoken and written text , 1988, IEEE Trans. Acoust. Speech Signal Process..
[2] Manfred Schlett. Trends in Embedded-Microprocessor Design , 1998, Computer.
[3] G.D. Hillman. DSP56200: An algorithm-specific digital signal processor peripheral , 1987, Proceedings of the IEEE.
[4] S. Haykin,et al. Adaptive Filter Theory , 1986 .